The application of computer software programmes (like electronic platforms) and online connectivity in filling and executing trading orders in electronic financial markets based on a set of algos/ algorithms. Algorithms are usually developed by highly professional and sophisticated programmers at proprietary trading firms. These algorithms take into account an array of criteria to figure out when and where to trade, including prices, timing, quantity of an order, fill ratios, overall transaction costs, etc. Timing considerations, for example, define how quickly an order can be carried out, or what time exactly orders should be entered to guarantee the most favorable chance of execution. Fill ratios determine how likely an order is to be filled. All of these factors are taken into account when firms are developing and deploying trading algorithms. Although the terms “robo trading” and “high frequency trading” have now become somewhat interchangeably used, they do in reality imply different things.

Black-box trading (algo trading) is usually used to take large-scale views on asset prices, whereby a trader pre-decides which stocks to buy or sell, and then hands over to the algorithm the actual execution of trading orders (the timing of intraday trading and at what price). In turn, a high frequency trading (HFT) system is a special type of algo trading in which automated, small scale, probabilistic bets are placed to exploit structural inefficiencies. High frequency trading uses algorithms and super-fast computers to detect and take advantage of market movements and trends.

Algo trading is largely used by mutual funds, pension funds, and other institutional investors to slice sizable trades into smaller, manageable chunks in order to control market impact and risk. Implementing algo trading typically involves a range of strategies such as pair trading, delta neutral, arbitrage, trend following, mean reversion, scalping, and so on.

Algo trading is also known as algorithm trading, automated trading, or robo trading.